Yingda Xia
Impact in
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- Advanced Neural Network Applications
- Medical Image Segmentation Techniques
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- COVID-19 diagnosis using AI
- Radiomics and Machine Learning in Medical Imaging
Papers in
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- Advanced Neural Network Applications 8
- Medical Image Segmentation Techniques 7
- Advanced Image and Video Retrieval Techniques 1
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- COVID-19 diagnosis using AI 4
- Radiomics and Machine Learning in Medical Imaging 2
- Co-authors
- Alan Yuille (7 shared papers)Zhuotun Zhu (5 shared papers)Fengze Liu (4 shared papers)Daguang Xu (3 shared papers)Dong Yang (3 shared papers)Lequan Yu (2 shared papers)Jinzheng Cai (2 shared papers)Holger R. Roth (2 shared papers)
- Journals
- Medical Image Analysis (1 paper)IEEE Transactions on Neural Networks and Learning Systems (1 paper)2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (1 paper)arXiv (Cornell University) (3 papers)
- Partner nations
- United StatesChinaHong Kong
In The Last Decade
Yingda Xia
11 papers receiving 522 citations
Peers
Comparison fields: 5 of 59
- Computer Vision and Pattern Recognition 317
- Radiology, Nuclear Medicine and Imaging 234
- Artificial Intelligence 274
- Health Informatics 10
- Neurology 60
Countries citing papers authored by Yingda Xia
This map shows the geographic impact of Yingda Xia's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Yingda Xia with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yingda Xia more than expected).
Fields of papers citing papers by Yingda Xia
This network shows the impact of papers produced by Yingda Xia. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Yingda Xia. The network helps show where Yingda Xia may publish in the future.
Co-authors
The 25 scholars most cited alongside Yingda Xia, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 163 | |
| 2 | 2022 | 117 | |
| 3 | 2018 | 95 | |
| 4 | 2020 | 93 | |
| 5 | 2023 | 19 | |
| 6 | A 3D Coarse-to-Fine Framework for Automatic Pancreas Segmentation. | 2017 | 17 |
| 7 | 2019 | 10 | |
| 8 | 2024 | 4 | |
| 9 | Thickened 2D Networks for 3D Medical Image Segmentation. | 2019 | 3 |
| 10 | Bridging the Gap Between 2D and 3D Organ Segmentation. | 2018 | 2 |
| 11 | 2024 | 2 |
About Yingda Xia
Yingda Xia is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Pulmonary and Respiratory Medicine and Biomedical Engineering, having authored 11 papers that have together received 525 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (8 papers), Medical Image Segmentation Techniques (7 papers), COVID-19 diagnosis using AI (4 papers), Domain Adaptation and Few-Shot Learning (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), AI in cancer detection (1 paper), Advanced Image and Video Retrieval Techniques (1 paper) and Lung Cancer Diagnosis and Treatment (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (317 citations), Radiology, Nuclear Medicine and Imaging (234 citations), Artificial Intelligence (274 citations), Health Informatics (10 citations) and Neurology (60 citations). Yingda Xia has collaborated with scholars based in United States, China and Hong Kong. Frequent co-authors include Alan Yuille, Zhuotun Zhu, Fengze Liu, Daguang Xu, Dong Yang, Lequan Yu, Jinzheng Cai, Holger R. Roth, Elliot K. Fishman and Wei Shen. Their work appears in journals such as Medical Image Analysis, IEEE Transactions on Neural Networks and Learning Systems, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and arXiv (Cornell University).
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.